{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tqdm in d:\\program\\anaconda\\envs\\ai\\lib\\site-packages (4.46.0)\n",
      "Requirement already satisfied: lightgbm in d:\\program\\anaconda\\envs\\ai\\lib\\site-packages (2.3.0)\n",
      "Requirement already satisfied: numpy in d:\\program\\anaconda\\envs\\ai\\lib\\site-packages (from lightgbm) (1.17.4)\n",
      "Requirement already satisfied: scikit-learn in d:\\program\\anaconda\\envs\\ai\\lib\\site-packages (from lightgbm) (0.22.1)\n",
      "Requirement already satisfied: scipy in d:\\program\\anaconda\\envs\\ai\\lib\\site-packages (from lightgbm) (1.3.2)\n",
      "Requirement already satisfied: joblib>=0.11 in d:\\program\\anaconda\\envs\\ai\\lib\\site-packages (from scikit-learn->lightgbm) (0.14.1)\n"
     ]
    }
   ],
   "source": [
    "! pip install tqdm\n",
    "! pip install lightgbm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "from sklearn.metrics import mean_squared_error,explained_variance_score\n",
    "from sklearn.model_selection import KFold\n",
    "import lightgbm as lgb\n",
    "import math\n",
    "import os\n",
    "from joblib import Parallel, delayed\n",
    "\n",
    "test_data_path = '../data/A_testData0531.csv'\n",
    "route_order_folder_path = '../data/route_order_data'\n",
    "port_path = '../data/port.csv'\n",
    "result_path = '../result_server_20200624-changed-feature.csv'\n",
    "\n",
    "# import moxing as mox\n",
    "# OBS_RES_PATH =  \"s3://ship-eta/result/result_server_20200622.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_data_type(data, mode='train'):\n",
    "    if mode=='test':\n",
    "        data['onboardDate'] = pd.to_datetime(data['onboardDate'], infer_datetime_format=True)\n",
    "        data['temp_timestamp'] = data['timestamp']\n",
    "        data['ETA'] = None\n",
    "        data['creatDate'] = None\n",
    "    data['loadingOrder'] = data['loadingOrder'].astype(str)\n",
    "    data['timestamp'] = pd.to_datetime(data['timestamp'], infer_datetime_format=True)\n",
    "    data['longitude'] = data['longitude'].astype(float)\n",
    "    data['latitude'] = data['latitude'].astype(float)\n",
    "    data['speed'] = data['speed'].astype(float)\n",
    "    data['TRANSPORT_TRACE'] = data['TRANSPORT_TRACE'].astype(str)\n",
    "    return data\n",
    "\n",
    "def get_test_data_info(path):\n",
    "    data = pd.read_csv(path) \n",
    "    test_trace_set = data['TRANSPORT_TRACE'].unique()\n",
    "    test_order_belong_to_trace = {}\n",
    "    for item in test_trace_set:\n",
    "        orders = data[data['TRANSPORT_TRACE'] == item]['loadingOrder'].unique()\n",
    "        test_order_belong_to_trace[item] = orders\n",
    "    return format_data_type(data, mode='test'), test_trace_set, test_order_belong_to_trace\n",
    "\n",
    "test_data_origin, test_trace_set, test_order_belong_to_trace = get_test_data_info(test_data_path)\n",
    "\n",
    "def get_port_info():\n",
    "    port_data = {}\n",
    "    test_port_set = set()\n",
    "    for route in test_trace_set:\n",
    "        ports = route.split('-')\n",
    "        test_port_set = set.union(test_port_set, set(ports))\n",
    "    port_data_origin = pd.read_csv(port_path)\n",
    "    for item in port_data_origin.itertuples():\n",
    "        if getattr(item, 'TRANS_NODE_NAME') in test_port_set:\n",
    "            port_data[getattr(item, 'TRANS_NODE_NAME')] = {'LONGITUDE': getattr(item, 'LONGITUDE'),'LATITUDE': getattr(item, 'LATITUDE') }\n",
    "    return port_data\n",
    "port_data = get_port_info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_train_route_order_data(route):\n",
    "    route_order_data_path = os.path.join(route_order_folder_path, \"{}.csv\".format(route))\n",
    "    data = pd.read_csv(route_order_data_path, header=None\n",
    "           , names=['loadingOrder','timestamp','longitude','latitude','speed'])\n",
    "    if (data.shape[0] == 0):\n",
    "        print(\"error == \", route)\n",
    "    data['timestamp'] = pd.to_datetime(data['timestamp'], infer_datetime_format=True)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from math import radians, cos, sin, asin, sqrt\n",
    "def haversine(lon1, lat1, lon2, lat2): # 经度1，纬度1，经度2，纬度2 （十进制度数）\n",
    "    # 将十进制度数转化为弧度\n",
    "    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])\n",
    "    # haversine公式\n",
    "    dlon = lon2 - lon1 \n",
    "    dlat = lat2 - lat1 \n",
    "    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2\n",
    "    c = 2 * asin(sqrt(a)) \n",
    "    r = 6371 # 地球平均半径，单位为公里\n",
    "    return c * r * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def handle_train_data(order_info_set,start_longitude,start_latitude,dest_longitude,dest_latitude):\n",
    "    order_info_set = order_info_set.reset_index(drop=True)\n",
    "    #       获取起航时间\n",
    "    start_time = order_info_set['timestamp'].min()\n",
    "    start_index = 0\n",
    "    for (index, info_item) in order_info_set.iterrows():\n",
    "        if abs(info_item['longitude']-start_longitude) < 0.5 and abs(info_item['latitude']-start_latitude) < 0.5 and info_item['speed'] > 0:\n",
    "            start_time = max(start_time, info_item['timestamp'])\n",
    "            start_index = index\n",
    "            break \n",
    "#       获取到达目的地时间，这里需要用 GPS 判断\n",
    "    end_time = order_info_set['timestamp'].max()\n",
    "    end_index = order_info_set.size-1\n",
    "    for (index, info_item) in order_info_set.iterrows():\n",
    "        if abs(info_item['longitude'] - dest_longitude) < 0.3 and abs(info_item['latitude'] - dest_latitude) < 0.3:\n",
    "            end_time = min(end_time, info_item['timestamp'])\n",
    "            end_index = index\n",
    "            break\n",
    "#         修正起点终点逆序\n",
    "    if (end_time < start_time):\n",
    "        start_time,end_time = end_time,start_time\n",
    "        start_index,end_index = end_index,start_index\n",
    "#         算出航行用时\n",
    "    total_seconds = (end_time - start_time).total_seconds()\n",
    "#         人工截取前 40% 的数据   \n",
    "    order_info_set = order_info_set[start_index:end_index+1]\n",
    "    cut_size = math.ceil(order_info_set.shape[0]*0.4)\n",
    "    order_info_set = order_info_set[0:cut_size]\n",
    "#         截取数据\n",
    "    if (order_info_set.shape[0] > 100):\n",
    "        index = np.linspace(0, order_info_set.shape[0]-1, num=100,dtype=int).tolist()\n",
    "        order_info_set = order_info_set.iloc[index]     \n",
    "#         获取特征\n",
    "    tail_info = order_info_set.tail(1).values.tolist()[0]\n",
    "    head_info = order_info_set.head(1).values.tolist()[0]\n",
    "\n",
    "    dis_to_dest = haversine(tail_info[2],tail_info[3],dest_longitude,dest_latitude)\n",
    "\n",
    "    dis_to_start = haversine(tail_info[2],tail_info[3],start_longitude,start_latitude)\n",
    "\n",
    "    trace_dis = haversine(head_info[2],head_info[3],tail_info[2],tail_info[3])\n",
    "    trace_time=(pd.Timedelta(tail_info[1]-head_info[1])).total_seconds()\n",
    "    if trace_time==0:\n",
    "        trace_time=1\n",
    "    trace_mean_speed=trace_dis*3.6/trace_time\n",
    "\n",
    "    feature_temp = pd.DataFrame({'dis_to_dest':[dis_to_dest], 'dis_to_start':[dis_to_start], \n",
    "        'trace_mean_speed':[trace_mean_speed], 'label':[total_seconds]})\n",
    "\n",
    "    return feature_temp   \n",
    "\n",
    "def get_train_data(route_order_info, route,start_longitude,start_latitude,dest_longitude,dest_latitude):\n",
    "    order_list = route_order_info['loadingOrder'].unique()\n",
    "    print(route, order_list.shape)\n",
    "    \n",
    "    data_grouped = route_order_info.groupby('loadingOrder')\n",
    "\n",
    "    train_data = Parallel(n_jobs=8)(delayed(handle_train_data)\n",
    "                                    (group,start_longitude,start_latitude,dest_longitude,dest_latitude)\n",
    "                                    for name, group in tqdm(data_grouped))\n",
    "#     for name, group in tqdm(data_grouped):\n",
    "#         handle_train_data(group,start_longitude,start_latitude,dest_longitude,dest_latitude)\n",
    "#         break\n",
    "    train_data = pd.concat(train_data)\n",
    "    if (train_data.shape[0] < 10):\n",
    "        for i in range(5):\n",
    "            train_data = pd.concat([train_data,train_data])\n",
    "    \n",
    "    return train_data.reset_index(drop=True)\n",
    "\n",
    "def get_test_data(order,start_longitude,start_latitude,dest_longitude,dest_latitude):\n",
    "    order_info_set = test_data_origin[test_data_origin['loadingOrder'] == order]\n",
    "    order_info_set['timestamp'] = pd.to_datetime(order_info_set['timestamp'], infer_datetime_format=True)\n",
    "    tail_info = order_info_set.tail(1).values.tolist()[0]\n",
    "    head_info = order_info_set.head(1).values.tolist()[0]\n",
    "\n",
    "    dis_to_dest = haversine(tail_info[2],tail_info[3],dest_longitude,dest_latitude)\n",
    "\n",
    "    dis_to_start = haversine(tail_info[2],tail_info[3],start_longitude,start_latitude)\n",
    "\n",
    "    trace_dis = haversine(head_info[2],head_info[3],tail_info[2],tail_info[3])\n",
    "\n",
    "    trace_time=(pd.Timedelta(tail_info[1]-head_info[1])).seconds\n",
    "    if trace_time==0:\n",
    "        trace_time=1\n",
    "    trace_mean_speed=trace_dis*3.6/trace_time\n",
    "\n",
    "    feature_temp = pd.DataFrame({'dis_to_dest':[dis_to_dest], 'dis_to_start':[dis_to_start], \n",
    "        'trace_mean_speed':[trace_mean_speed]})\n",
    "\n",
    "    return feature_temp\n",
    "def mse_score_eval(preds, valid):\n",
    "    labels = valid.get_label()\n",
    "    scores = mean_squared_error(y_true=labels, y_pred=preds)\n",
    "    return 'mse_score', scores, True\n",
    "def train_model(x, y, seed=981125, is_shuffle=True):\n",
    "    train_pred = np.zeros((x.shape[0], ))\n",
    "    n_splits = min(5, x.shape[0])\n",
    "    # Kfold\n",
    "    fold = KFold(n_splits=n_splits, shuffle=is_shuffle, random_state=seed)\n",
    "    kf_way = fold.split(x)\n",
    "    # params\n",
    "    params = {\n",
    "        'learning_rate': 0.01,\n",
    "        'boosting_type': 'gbdt',\n",
    "        'objective': 'regression',\n",
    "        'num_leaves': 36,\n",
    "        'feature_fraction': 0.6,\n",
    "        'bagging_fraction': 0.7,\n",
    "        'bagging_freq': 6,\n",
    "        'seed': 8,\n",
    "        'bagging_seed': 1,\n",
    "        'feature_fraction_seed': 7,\n",
    "        'min_data_in_leaf': 25,\n",
    "        'nthread': 8,\n",
    "        'verbose': 1,\n",
    "    }\n",
    "    # train\n",
    "    for n_fold, (train_idx, valid_idx) in enumerate(kf_way, start=1):\n",
    "        train_x, train_y = x.iloc[train_idx], y.iloc[train_idx]\n",
    "        valid_x, valid_y = x.iloc[valid_idx], y.iloc[valid_idx]\n",
    "        # 数据加载\n",
    "        n_train = lgb.Dataset(train_x, label=train_y)\n",
    "        n_valid = lgb.Dataset(valid_x, label=valid_y)\n",
    "        clf = lgb.train(\n",
    "            params=params,\n",
    "            train_set=n_train,\n",
    "            num_boost_round=3000,\n",
    "            valid_sets=[n_valid],\n",
    "            early_stopping_rounds=100,\n",
    "            verbose_eval=100,\n",
    "            feval=mse_score_eval\n",
    "        )\n",
    "        train_pred[valid_idx] = clf.predict(valid_x, num_iteration=clf.best_iteration)\n",
    "    return clf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
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      "CNYTN-MXZLO (824,)\n"
     ]
    },
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.35921e+10\tvalid_0's mse_score: 5.35921e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.62995e+10\tvalid_0's mse_score: 6.62995e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.7363e+10\tvalid_0's mse_score: 2.7363e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.53865e+10\tvalid_0's mse_score: 3.53865e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.46996e+10\tvalid_0's mse_score: 5.46996e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.46287e+10\tvalid_0's mse_score: 6.46287e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.45325e+10\tvalid_0's mse_score: 2.45325e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.34234e+10\tvalid_0's mse_score: 3.34234e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.56594e+10\tvalid_0's mse_score: 4.56594e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.43253e+10\tvalid_0's mse_score: 5.43253e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  5%|▍         | 1/22 [04:12<1:28:29, 252.82s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNSHK-MYTPP (7577,)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.44692e+09\tvalid_0's mse_score: 7.44692e+09\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.38973e+10\tvalid_0's mse_score: 1.38973e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.95856e+10\tvalid_0's mse_score: 1.95856e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.80664e+10\tvalid_0's mse_score: 2.80664e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.34824e+10\tvalid_0's mse_score: 1.34824e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.0824e+10\tvalid_0's mse_score: 2.0824e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 6.39521e+09\tvalid_0's mse_score: 6.39521e+09\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.32472e+10\tvalid_0's mse_score: 1.32472e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.54452e+10\tvalid_0's mse_score: 2.54452e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.40048e+10\tvalid_0's mse_score: 3.40048e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  9%|▉         | 2/22 [21:46<2:44:20, 493.03s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNSHK-SGSIN (7581,)\n"
     ]
    },
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     "output_type": "stream",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.64791e+10\tvalid_0's mse_score: 1.64791e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.61781e+10\tvalid_0's mse_score: 2.61781e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.45165e+10\tvalid_0's mse_score: 1.45165e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.14421e+10\tvalid_0's mse_score: 2.14421e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.9775e+10\tvalid_0's mse_score: 1.9775e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.86977e+10\tvalid_0's mse_score: 2.86977e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
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      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "text": [
      "CNSHK-CLVAP (69,)\n"
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 8.86018e+12\tvalid_0's mse_score: 8.86018e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 8.86018e+12\tvalid_0's mse_score: 8.86018e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.56701e+12\tvalid_0's mse_score: 5.56701e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.56701e+12\tvalid_0's mse_score: 5.56701e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.29846e+12\tvalid_0's mse_score: 7.29846e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 7.29846e+12\tvalid_0's mse_score: 7.29846e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 9.65999e+12\tvalid_0's mse_score: 9.65999e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 9.65999e+12\tvalid_0's mse_score: 9.65999e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.57612e+12\tvalid_0's mse_score: 5.57612e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.57612e+12\tvalid_0's mse_score: 5.57612e+12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
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     "text": [
      "CNYTN-ARENA (82,)\n"
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 9.80012e+12\tvalid_0's mse_score: 9.80012e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 9.80012e+12\tvalid_0's mse_score: 9.80012e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.01517e+13\tvalid_0's mse_score: 1.01517e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.01517e+13\tvalid_0's mse_score: 1.01517e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.0279e+13\tvalid_0's mse_score: 1.0279e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.0279e+13\tvalid_0's mse_score: 1.0279e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.03959e+13\tvalid_0's mse_score: 1.03959e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.03959e+13\tvalid_0's mse_score: 1.03959e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.09589e+13\tvalid_0's mse_score: 1.09589e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.09589e+13\tvalid_0's mse_score: 1.09589e+13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "text": [
      "CNYTN-MATNG (1917,)\n"
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    },
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.79947e+10\tvalid_0's mse_score: 2.79947e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.35397e+10\tvalid_0's mse_score: 4.35397e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.665e+10\tvalid_0's mse_score: 2.665e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.47858e+10\tvalid_0's mse_score: 4.47858e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.20745e+10\tvalid_0's mse_score: 3.20745e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.41098e+10\tvalid_0's mse_score: 4.41098e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.27269e+10\tvalid_0's mse_score: 3.27269e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.96602e+10\tvalid_0's mse_score: 4.96602e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.11535e+10\tvalid_0's mse_score: 5.11535e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 7.20055e+10\tvalid_0's mse_score: 7.20055e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
    },
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     "output_type": "stream",
     "text": [
      "CNSHK-GRPIR (115,)\n"
     ]
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.40117e+10\tvalid_0's mse_score: 2.40117e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.07375e+10\tvalid_0's mse_score: 3.07375e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.01277e+10\tvalid_0's mse_score: 7.01277e+10\n",
      "Early stopping, best iteration is:\n",
      "[14]\tvalid_0's l2: 6.67913e+10\tvalid_0's mse_score: 6.67913e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.73302e+11\tvalid_0's mse_score: 1.73302e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.84165e+11\tvalid_0's mse_score: 1.84165e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.06448e+10\tvalid_0's mse_score: 4.06448e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.23148e+10\tvalid_0's mse_score: 4.23148e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.20219e+11\tvalid_0's mse_score: 1.20219e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.38973e+11\tvalid_0's mse_score: 1.38973e+11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "output_type": "stream",
     "text": [
      "CNSHK-PKQCT (315,)\n"
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 8.18765e+09\tvalid_0's mse_score: 8.18765e+09\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.44397e+10\tvalid_0's mse_score: 1.44397e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.55209e+10\tvalid_0's mse_score: 1.55209e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
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      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 9.72979e+09\tvalid_0's mse_score: 9.72979e+09\n",
      "Early stopping, best iteration is:\n",
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      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.87186e+10\tvalid_0's mse_score: 1.87186e+10\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "text": [
      "COBUN-HKHKG (298,)\n"
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    },
    {
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.56594e+10\tvalid_0's mse_score: 1.56594e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.65446e+10\tvalid_0's mse_score: 1.65446e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.0491e+10\tvalid_0's mse_score: 4.0491e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.14896e+10\tvalid_0's mse_score: 4.14896e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.70733e+09\tvalid_0's mse_score: 7.70733e+09\n",
      "Early stopping, best iteration is:\n",
      "[54]\tvalid_0's l2: 7.22075e+09\tvalid_0's mse_score: 7.22075e+09\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.44305e+11\tvalid_0's mse_score: 1.44305e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.42199e+11\tvalid_0's mse_score: 1.42199e+11\n",
      "Training until validation scores don't improve for 100 rounds\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      " 41%|████      | 9/22 [1:00:37<46:11, 213.22s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[100]\tvalid_0's l2: 3.0164e+10\tvalid_0's mse_score: 3.0164e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.21165e+10\tvalid_0's mse_score: 3.21165e+10\n",
      "CNYTN-PAONX (528,)\n"
     ]
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    {
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.40137e+11\tvalid_0's mse_score: 1.40137e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.81033e+11\tvalid_0's mse_score: 1.81033e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 9.45151e+10\tvalid_0's mse_score: 9.45151e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.54544e+11\tvalid_0's mse_score: 1.54544e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.0394e+11\tvalid_0's mse_score: 1.0394e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.83924e+11\tvalid_0's mse_score: 1.83924e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.49217e+10\tvalid_0's mse_score: 5.49217e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.33119e+11\tvalid_0's mse_score: 1.33119e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.85158e+10\tvalid_0's mse_score: 7.85158e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.59832e+11\tvalid_0's mse_score: 1.59832e+11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNSHK-SIKOP (555,)\n"
     ]
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.22997e+10\tvalid_0's mse_score: 3.22997e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.20762e+11\tvalid_0's mse_score: 1.20762e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.88689e+10\tvalid_0's mse_score: 3.88689e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.43317e+11\tvalid_0's mse_score: 1.43317e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.72418e+10\tvalid_0's mse_score: 4.72418e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.82982e+11\tvalid_0's mse_score: 1.82982e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.33316e+10\tvalid_0's mse_score: 3.33316e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.20021e+11\tvalid_0's mse_score: 1.20021e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.12482e+10\tvalid_0's mse_score: 4.12482e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.49958e+11\tvalid_0's mse_score: 1.49958e+11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNYTN-CAVAN (178,)\n"
     ]
    },
    {
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.528e+10\tvalid_0's mse_score: 1.528e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.13328e+10\tvalid_0's mse_score: 2.13328e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.72245e+10\tvalid_0's mse_score: 1.72245e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.5019e+10\tvalid_0's mse_score: 2.5019e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.09644e+10\tvalid_0's mse_score: 3.09644e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.10194e+10\tvalid_0's mse_score: 4.10194e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.52281e+10\tvalid_0's mse_score: 2.52281e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.43977e+10\tvalid_0's mse_score: 3.43977e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.38494e+10\tvalid_0's mse_score: 1.38494e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.36054e+10\tvalid_0's mse_score: 2.36054e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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    {
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     "text": [
      "CNSHK-ESALG (62,)\n"
     ]
    },
    {
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      "\n",
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     ]
    },
    {
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.52278e+12\tvalid_0's mse_score: 4.52278e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.52278e+12\tvalid_0's mse_score: 4.52278e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.8663e+12\tvalid_0's mse_score: 4.8663e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.8663e+12\tvalid_0's mse_score: 4.8663e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.98795e+12\tvalid_0's mse_score: 4.98795e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.53441e+12\tvalid_0's mse_score: 5.53441e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.53441e+12\tvalid_0's mse_score: 5.53441e+12\n",
      "Training until validation scores don't improve for 100 rounds\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "text": [
      "[100]\tvalid_0's l2: 5.5097e+12\tvalid_0's mse_score: 5.5097e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.5097e+12\tvalid_0's mse_score: 5.5097e+12\n",
      "CNYTN-MTMLA (920,)\n"
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.21228e+10\tvalid_0's mse_score: 5.21228e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.74734e+10\tvalid_0's mse_score: 6.74734e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.96908e+10\tvalid_0's mse_score: 3.96908e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.07825e+10\tvalid_0's mse_score: 5.07825e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 9.32773e+10\tvalid_0's mse_score: 9.32773e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.17286e+11\tvalid_0's mse_score: 1.17286e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.39105e+10\tvalid_0's mse_score: 4.39105e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.37162e+10\tvalid_0's mse_score: 6.37162e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.91048e+10\tvalid_0's mse_score: 3.91048e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.27155e+10\tvalid_0's mse_score: 5.27155e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNSHK-ZADUR (588,)\n"
     ]
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    {
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.08323e+10\tvalid_0's mse_score: 1.08323e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.7156e+10\tvalid_0's mse_score: 1.7156e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.08098e+10\tvalid_0's mse_score: 3.08098e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.92053e+10\tvalid_0's mse_score: 3.92053e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.12307e+10\tvalid_0's mse_score: 1.12307e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.95171e+10\tvalid_0's mse_score: 1.95171e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.77229e+10\tvalid_0's mse_score: 2.77229e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.69673e+10\tvalid_0's mse_score: 3.69673e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.02838e+10\tvalid_0's mse_score: 1.02838e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.83496e+10\tvalid_0's mse_score: 1.83496e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     "text": [
      "CNSHK-LBBEY (89,)\n"
     ]
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    {
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.34103e+12\tvalid_0's mse_score: 4.34103e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.34103e+12\tvalid_0's mse_score: 4.34103e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.75694e+12\tvalid_0's mse_score: 3.75694e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.75694e+12\tvalid_0's mse_score: 3.75694e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 3.68558e+12\tvalid_0's mse_score: 3.68558e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.68558e+12\tvalid_0's mse_score: 3.68558e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.89708e+12\tvalid_0's mse_score: 4.89708e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.89708e+12\tvalid_0's mse_score: 4.89708e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 6.48408e+11\tvalid_0's mse_score: 6.48408e+11"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
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    {
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     "output_type": "stream",
     "text": [
      "\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.5776e+11\tvalid_0's mse_score: 6.5776e+11\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "CNSHA-SGSIN (33,)\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "\n",
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     ]
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    {
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     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.6416e+11\tvalid_0's mse_score: 2.6416e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.6416e+11\tvalid_0's mse_score: 2.6416e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.92059e+11\tvalid_0's mse_score: 2.92059e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.92059e+11\tvalid_0's mse_score: 2.92059e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.14088e+11\tvalid_0's mse_score: 2.14088e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.14088e+11\tvalid_0's mse_score: 2.14088e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.86346e+11\tvalid_0's mse_score: 1.86346e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.86346e+11\tvalid_0's mse_score: 1.86346e+11\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.11791e+11\tvalid_0's mse_score: 2.11791e+11\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.11791e+11\tvalid_0's mse_score: 2.11791e+11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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    {
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     "text": [
      "CNYTN-RTM (24,)\n"
     ]
    },
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      "\n",
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 6.98214e+12\tvalid_0's mse_score: 6.98214e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.98214e+12\tvalid_0's mse_score: 6.98214e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.46901e+12\tvalid_0's mse_score: 7.46901e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 7.46901e+12\tvalid_0's mse_score: 7.46901e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 7.34699e+12\tvalid_0's mse_score: 7.34699e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 7.34699e+12\tvalid_0's mse_score: 7.34699e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 5.45628e+12\tvalid_0's mse_score: 5.45628e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.45628e+12\tvalid_0's mse_score: 5.45628e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 6.78294e+12\tvalid_0's mse_score: 6.78294e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.78294e+12\tvalid_0's mse_score: 6.78294e+12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNHKG-MXZLO (835,)\n"
     ]
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    },
    {
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 4.56353e+10\tvalid_0's mse_score: 4.56353e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.59837e+10\tvalid_0's mse_score: 5.59837e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.38683e+10\tvalid_0's mse_score: 4.38683e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
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      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.79857e+10\tvalid_0's mse_score: 5.79857e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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     ]
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     "output_type": "stream",
     "text": [
      "\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 4.18311e+10\tvalid_0's mse_score: 4.18311e+10\n"
     ]
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     "text": [
      "HKHKG-FRFOS (80,)\n"
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     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 6.69498e+12\tvalid_0's mse_score: 6.69498e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.69498e+12\tvalid_0's mse_score: 6.69498e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
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      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.2636e+12\tvalid_0's mse_score: 5.2636e+12\n",
      "Training until validation scores don't improve for 100 rounds\n",
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      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 5.68867e+12\tvalid_0's mse_score: 5.68867e+12\n",
      "Training until validation scores don't improve for 100 rounds\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      " 91%|█████████ | 20/22 [1:19:14<03:15, 97.77s/it] "
     ]
    },
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     "output_type": "stream",
     "text": [
      "[100]\tvalid_0's l2: 6.32457e+12\tvalid_0's mse_score: 6.32457e+12\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 6.32457e+12\tvalid_0's mse_score: 6.32457e+12\n"
     ]
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      "CNYTN-NZAKL (140,)\n"
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.37811e+10\tvalid_0's mse_score: 1.37811e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 2.47334e+10\tvalid_0's mse_score: 2.47334e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.86814e+10\tvalid_0's mse_score: 2.86814e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.90239e+10\tvalid_0's mse_score: 3.90239e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 8.0941e+09\tvalid_0's mse_score: 8.0941e+09\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.2948e+10\tvalid_0's mse_score: 1.2948e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.32982e+10\tvalid_0's mse_score: 1.32982e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.84274e+10\tvalid_0's mse_score: 1.84274e+10\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 2.32016e+10\tvalid_0's mse_score: 2.32016e+10\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 3.41055e+10\tvalid_0's mse_score: 3.41055e+10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      " 95%|█████████▌| 21/22 [1:19:32<01:13, 73.71s/it]\n",
      "100%|██████████| 1/1 [00:00<00:00, 200.98it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNSHA-PAMIT (1,)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Training until validation scores don't improve for 100 rounds\n",
      "[100]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l2: 1.15783e+13\tvalid_0's mse_score: 1.15783e+13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Program\\Anaconda\\envs\\AI\\lib\\site-packages\\ipykernel_launcher.py:73: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "100%|██████████| 22/22 [1:19:34<00:00, 217.03s/it]\n"
     ]
    }
   ],
   "source": [
    "for route in tqdm(test_order_belong_to_trace):\n",
    "    ports = route.split(\"-\")\n",
    "    start_port = ports[0]\n",
    "    dest_port = ports[-1]\n",
    "    start_longitude = port_data[start_port]['LONGITUDE']\n",
    "    start_latitude = port_data[start_port]['LATITUDE']\n",
    "    dest_longitude = port_data[dest_port]['LONGITUDE']\n",
    "    dest_latitude = port_data[dest_port]['LATITUDE']\n",
    "    \n",
    "    route_order_info = get_train_route_order_data(route)\n",
    "    train_data = get_train_data(route_order_info, route,start_longitude,start_latitude,dest_longitude,dest_latitude)\n",
    "#     print(train_data)\n",
    "    \n",
    "    features = [c for c in train_data.columns if c not in ['loadingOrder', 'label']]\n",
    "    model_by_route = train_model(train_data[features], train_data['label'])\n",
    "    \n",
    "    for order in test_order_belong_to_trace[route]:\n",
    "        test_order_data = get_test_data(order,start_longitude,start_latitude,dest_longitude,dest_latitude)\n",
    "\n",
    "        res = model_by_route.predict(test_order_data[features], num_iteration=model_by_route.best_iteration)\n",
    "        test_data_origin.loc[test_data_origin['loadingOrder'] == order, 'ETA'] = (test_data_origin[test_data_origin['loadingOrder'] == order]['onboardDate'] + pd.Timedelta(seconds=res[0])).apply(lambda x:x.strftime('%Y/%m/%d  %H:%M:%S'))\n",
    "        \n",
    "test_data_origin['creatDate'] = pd.datetime.now().strftime('%Y/%m/%d  %H:%M:%S')\n",
    "test_data_origin['timestamp'] = test_data_origin['temp_timestamp']\n",
    "\n",
    "result = test_data_origin[['loadingOrder', 'timestamp', 'longitude', 'latitude', 'carrierName', 'vesselMMSI', 'onboardDate', 'ETA', 'creatDate']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_csv(result_path, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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